Nex AGI: Nex-N2.5-Mini vs Z.ai: GLM 5.1: Live Promos, Pricing, Hidden Fees & Latency
Verified 2026 FinOps benchmark comparing Nex AGI: Nex-N2.5-Mini (nex-agi/nex-n2.5-mini) vs Z.ai: GLM 5.1 (z-ai/glm-5.1). Simulate cache read multipliers, context cliffs, MAU bills, and P90 latency.
Nex AGI: Nex-N2.5-Mini (nex-agi/nex-n2.5-mini) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Nex AGI: Nex-N2.5-Mini: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.0125/1M) or route via asynchronous Batch API for 50% off standard token rates.
Z.ai: GLM 5.1 (z-ai/glm-5.1) 2026 Q4 Developer Promotion & Volume Credits
Official 2026 Q4 promotion for Z.ai: GLM 5.1: Activate ephemeral prefix caching to slash input costs by 50% (down to $0.483/1M) or route via asynchronous Batch API for 50% off standard token rates.
In Etuki October 2026 FinOps telemetry comparing Nex AGI: Nex-N2.5-Mini (API ID: nex-agi/nex-n2.5-mini) vs Z.ai: GLM 5.1 (API ID: z-ai/glm-5.1), Nex AGI: Nex-N2.5-Mini offers lower standard input pricing at $0.025/1M tokens ($0.1/1M output), while Nex AGI: Nex-N2.5-Mini leads in cached prefix economics at $0.0125/1M tokens (50% discount). Nex AGI: Nex-N2.5-Mini achieves a 0ms faster P90 time-to-first-token latency (280ms vs 280ms).
Auto-discovered via live global telemetry registry.
Auto-discovered via live global telemetry registry.
| Specification / FinOps Dimension | Nex AGI: Nex-N2.5-Mini | Z.ai: GLM 5.1 | Verified Advantage |
|---|---|---|---|
| Official Vendor API ID | nex-agi/nex-n2.5-mini | z-ai/glm-5.1 | Pinned Snapshot IDs |
| Standard Input / Output (per 1M) | $0.025 / $0.1 | $0.966 / $3.036 | Nex AGI: Nex-N2.5-Mini |
| Cache Read Price (per 1M) | $0.0125/1M (50% Off) | $0.483/1M (50% Off) | Nex AGI: Nex-N2.5-Mini |
| Context Window / Max Output | 256K In / 230K Out | 200K In / 125K Out | Nex AGI: Nex-N2.5-Mini |
| P90 First-Token / Edge Latency | 280ms | 280ms | Nex AGI: Nex-N2.5-Mini (-0ms) |
Nex-N2.5 is an agentic model built to turn goals into working, verified outcomes. Its core strength is agentic coding within a visual feedback loop: it can explore codebases, imple
GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interaction
Real-Time Stack Cost & Hidden-Fee Simulator (MAU / Token / Egress / GMV)
Calibrated with Reddit r/FinOps & r/devops telemetry: Includes Context Caching, Bandwidth Egress, and MoR Tax
🛰️Switch from Nex AGI: Nex-N2.5-Mini to Z.ai: GLM 5.1
GLM-5.1 delivers a major leap in coding capability, with particularly significant gains in handling long-horizon tasks. Unlike previous models built around minute-level interaction Verified P90 latency of 280ms.